


AO3 Ship Stats: Time Series 2013-2020

by centreoftheselights



Series: AO3 Ship Stats [14]
Category: Fandom - Fandom, No Fandom
Genre: AO3 Research, AO3 Statistics, Character(s) of Color, Data - Freeform, Fan Studies, Fandom Research, Fandom Statistics, Graphs, Meta, Meta Essay, Nonfiction, People of Color, Racism, Racism in fandom, acafandom, fandom essays, statistics
Language: English
Status: Completed
Published: 2020-11-06
Updated: 2020-12-15
Packaged: 2021-03-08 17:33:48
Rating: General Audiences
Warnings: No Archive Warnings Apply
Chapters: 4
Words: 2,554
Publisher: archiveofourown.org
Story URL: https://archiveofourown.org/works/27420499
Author URL: https://archiveofourown.org/users/centreoftheselights/pseuds/centreoftheselights
Summary: A collection of graphs showing the variation over time of various features of the AO3 Ship Stats.
Series: AO3 Ship Stats [14]
Series URL: https://archiveofourown.org/series/1209645
Comments: 21
Kudos: 104





	1. Fandom Types

**Author's Note:**

> This analysis is ongoing. If you have any particular graphs you want to see, let me know in the comments and, where feasible, I'll post a chapter with the results!
> 
> All data is derived from the AO3 Ship Stats lists as published in the period 2013-2020.

[Transcription: A stacked graph titled "Fandom Types in the AO3 Ship Stats Overall List." For each year, the total of all data points is equal to 100.

Years: 2013/2014/2015/2016/2017/2019/2020  
TV Shows: 44.33/45/43/38.5/33.5/34/32.17  
Movies: 22.83/21.83/20.83/22.83/22.33/23.83/25.33  
Books & Literature: 10.5/8.83/7.83/8.33/8.33/8.33/10  
Western Animation: 2.33/0/0/1/2.5/3.5/3.5  
Anime & Manga: 2/4/8/8/13/11/12.33  
Video Games: 0/0/2/5/2/3/1.33  
Webcomics: 5/5/4/3/1/0/0  
Theater: 1/0.33/0.33/0.33/1.33/1.33/0.33  
Music & Bands: 11/11/9/8/12/13/13  
Celebrities & Real People: 1/3/3/3/2/2/2  
Other Media: 0/1/2/2/2/0/0]

Fandoms on AO3 are sorted into one of ten possible types. Over the period 2013-2020, the relative number of pairings from each of these types represented on the Overall AO3 Ship Stats list has remained relatively stable, although the number of pairings from TV Shows has decreased somewhat while the popularity of Anime & Manga has risen, especially around 2015-2017.

(N.B. Where fandoms have significant works in more than one type - e.g. Harry Potter, which could be considered both Books & Literature and Movies - the number of pairings is divided evenly between up to 3 relevant types, including fractions where necessary.)

[Transcription: A stacked graph titled "Fandom Types in the AO3 Ship Stats Yearly List." For each year, the total of all data points is equal to 100.

Years: 2016/2017/2019/2020  
TV Shows: 32/35/29.83/16  
Movies: 19.33/15.5/20/20  
Books & Literature: 7.83/7.5/8.83/11.5  
Western Animation: 3.5/5/8.5/6  
Anime & Manga: 10.5/10/10.33/21.67  
Video Games: 7/6/5/5.33  
Webcomics: 2.5/1/0/0  
Theater: 1.33/4/1/0  
Music & Bands: 11/12/14.5/14.5  
Celebrities & Real People: 4/4/1/2  
Other Media: 1/0/1/3]

It is only possible to calculate the Yearly list (showing the pairings with the greatest increase in work count between two sets of statistics) from 2016 onwards. Although these lists tend to have greater variation in which pairings appear, the relative popularity of fandom types remained stable once more, except for a sharp decrease in TV Shows in 2020, with a corresponding increase in Anime & Manga.


	2. Fandom Fic Totals

The following charts show data for the combined work total of each fandom for **all** pairings associated with that fandom that fell into the top 100. To keep numbers comparable from year to year, each year's data has been normalised by the number of works of the pairing at position #100 on the list. Each chart is shown with both a linear and a logarithmic y-axis, and each data set shows the 20 fandoms with the largest average score across the period shown.

[Transcription: Two graphs headed "Fandom Fic Total in the AO3 Ship Stats Overall Top 100 (Normalised By Position #100 Fics)". The graphs display the same data, with the only difference being that the second plot uses a logarithmic y axis. The data is as follows:

Year: 2013/2014/2015/2016/2017/2019/2020  
Supernatural: 45.98/47.08/45.71/38.47/34.60/29.12/25.20  
MCU: 33.20/32.48/34.40/31.05/25.64/30.22/29.18  
Sherlock: 41.43/40.35/35.86/28.00/23.65/18.75/15.06  
Teen Wolf: 29.20/32.31/30.30/22.31/15.48/13.12/11.36  
Harry Potter: 26.62/21.66/18.48/16.32/16.53/17.17/17.04  
One Direction: 16.36/22.31/21.45/15.58/12.16/7.80/6.47  
Merlin: 11.58/8.80/8.39/5.70/4.66/3.97/2.87  
Stargate: 14.94/10.48/7.86/5.81/2.77/2.15/1.84  
Bangtan Boys: 0/0/0/1.11/7.45/17.48/17.98  
Doctor Who: 10.58/9.17/6.50/5.18/3.46/3.37/2.96  
Star Trek: 9.56/9.00/6.42/4.76/4.17/3.44/3.05  
Glee: 11.42/7.89/7.04/4.67/3.73/2.88/2.49  
Once Upon A Time: 3.52/5.22/6.65/6.92/6.40/5.55/4.69  
Shingeki no Kyojin: 0/5.74/7.73/6.90/5.77/3.70/2.20  
Bandom: 6.67/3.81/3.98/4.98/4.88/4.12/2.56  
X-Men Movies: 6.71/5.18/4.70/3.74/3.10/2.53/2.26  
Homestuck: 8.43/7.17/5.55/3.78/1.18/0/0  
The Sentinel: 8.90/5.63/3.35/2.26/1.71/1.35/1.13  
Hawaii Five-0: 6.67/4.69/3.59/2.70/2.30/2.06/1.81  
Les Miserables: 6.11/4.40/3.76/2.86/2.31/1.88/1.63]

Comparing the fandom fic totals on the Overall lists, we can see a strong pattern emerging, where each fandom's work count tends to decrease in an approximately-exponential decay from year to year. A few fandoms buck this trend - Bangtan Boys climbed rapidly from 2016-2020, where they were the third biggest fandom listed, the MCU experienced relatively shallower growth in 2014-2015 and 2017-2019, and Homestuck fell off sharply from 2017 onwards - but in general, most of the deviations are relatively small.

The meaning of this pattern is that a fandom, once established enough to have multiple pairings on the overall top 100 list, tends to have enough "momentum" to maintain its place on the list for many years, falling off only gradually as newer fandoms slowly gain ground. It is important to consider which "megafandoms" are ascending the list today, as these fandoms are likely to remain a feature for many years into the future.

[Transcription: Two graphs headed "Fandom Fic Total in the AO3 Ship Stats Yearly Top 100 (Normalised By Position #100 Fics)". The graphs display the same data, with the only difference being that the second plot uses a logarithmic y axis. The data is as follows:

Year: 2016/2017/2019/2020  
MCU: 21.98/12.64/32.22/24.42  
Bangtan Boys: 9.22/21.70/28.94/20.64  
Supernatural: 26.55/21.82/10.70/5.91  
Harry Potter: 9.98/17.67/12.55/15.35  
Boku no Hero Academia: 0/0/15.82/27.94  
Star Wars: 11.00/7.45/7.64/10.97  
Voltron: 0/15.02/17.50/3.20  
Sherlock: 11.25/10.19/5.49/1.60  
Yuri!!! on Ice: 0/20.69/5.18/1.39  
Haikyuu!!: 12.47/6.96/0/6.56  
Good Omens: 0/0/5.06/19.44  
Arrowverse: 5.22/10.17/4.70/2.72  
Teen Wolf: 7.73/4.80/6.20/2.45  
Youtube RPF: 7.60/6.14/2.61/1.34  
The 100: 10.99/4.08/2.44/0  
Shadowhunters: 3.34/5.18/5.37/2.71  
Miraculous Ladybug: 3.77/2.50/3.80/3.91  
Modao Zushi: 0/0/1.15/12.20  
Once Upon A Time: 7.21/4.75/1.08/0  
IT: 0/0/1.76/9.04]

In comparison, the same data from the Yearly lists is far more chaotic. This is to be expected, both as there are fewer data points to establish a pattern, and because the Yearly lists generally have more variation and a higher turnover of pairings, since there is a lower barrier to entry for new fandoms. A number of fandoms do show a consistent downwards trend like those on the Overall lists, Supernatural and Sherlock being two examples; however, many other fandoms show significant upwards trends (e.g. Good Omens, Boku no Hero Academia) while others display a mix of growth and decay (e.g. Yuri!!! on Ice and Shadowhunters).


	3. People of Colour

The AO3 Ship Stats has been recording race since 2014, although in that time it has become clear that for some characters, there is no definitive way to classify their race. Generally, a character's race is classified according to first, statements made in canon about their race; second, "Word of God" statements made outside of canon; third, the racial background of the actor physically portraying them (where relevant); and fourth, an educated reading of any canon clues that might suggest their racial background.

If the character is clearly non-white but no definite race can be decided (e.g. the character is animated, or the setting does not use recognisable racial categories) they are placed in the "Fantasy Races" category. "Ambiguous" refers to characters whose race is explicitly left ambiguous; whose race varies between adaptations of the work; or who have non-human skin tones such as green or blue. For characters who belong to multiple of the racial categories considered due to being mixed race or non-white Latino, their number of appearances on the list is split equally by the number of categories they belong to.

For comparison purposes, the full list contains 100 pairings, i.e. 200 characters in total.

[Transcription: A stacked line graph headed "POC in the AO3 Ship Stats Overall List" displaying the following data:

Year: 2013/2014/2015/2016/2017/2019/2020  
Asian (Asian Media): 2/0/8/10/25/30/40  
Asian (Western Media): 3/4/6/5.5/5.5/6.5/5.5  
Latino: 3.5/5.5/5.5/4.5/7.5/6.5/4.5  
Black: 4.5/3.5/3.5/3/2/2/1  
Middle Eastern: 1/0/0/1/1/1/1  
Fantasy Races: 0/0/1/3/0/0/0  
Indigenous: 2/0/0/0/0/0/0  
Ambig: 11/12/12/15/10/8/7]

[Transcription: A stacked line graph headed "POC in the AO3 Ship Stats Yearly List" displaying the following data:

Year: 2016/2017/2019/2020  
Asian (Asian Media): 28/34/49/77  
Asian (Western Media): 6.5/12/8/5.5  
Latino: 4.5/11/6/4.5  
Black: 3.5/2.5/0/2  
Middle Eastern: 2.5/2.5/0/1  
Fantasy Races: 3/0/0/0  
Indigenous Peoples: 1/0/1/2  
Ambig: 15/11/11/7]

For the purposes of demonstration, the presence of Asian characters has been divided by the origin of the media in question, distinguishing Asian characters in Western media from those in media made in majority-Asian countries such as Japan, China and Korea. There has been a huge surge in popularity of anime, manga and K-Pop fandoms on AO3 from 2016 onwards. This does not necessarily represent new fandoms - anime and manga have always had a significant presence among online fanfic - but is more likely to be due to migration from other websites such as FanFiction.Net and WattPad.

As I have highlighted before in my essay "[Fandom's Race Problem and the AO3 Ship Stats](https://archiveofourown.org/works/16976571)" this rise in Asian media fandom has created a trend of rising numbers of POC on the overall list which - although accurate overall - hides that the presence of POC within the popular pairings of Western media fandom has remained constant or - in the case of Black characters - fallen over the period surveyed. In order to avoid contributing to the silencing of people of Colour in fandom circles, I intend to begin presenting the racial data on the main list differently going forwards to more clearly recognise this distinction. I would welcome any suggestions or feedback on how best to achieve this in the comments.


	4. Ship Demographics

The following graphs show the breakdowns of the Top 100 lists by the gender and race categories commonly used on the AO3 Ship Stats lists, i.e. M/M, F/M, F/F and White, Whi/POC, POC etc.

[Transcription: a stacked line graph titled "Ship Gender and Ethnicity in the AO3 Ship Stats Overall List. The data is as follows:

Year: 2013/2014/2015/2016/2017/2019/2020  
White M/M: 56/59/50/46/44/43/40  
Whi/POC M/M: 8/7/7/6/8/8/6  
POC M/M: 1/0/4/6/13/16/20  
White F/M: 17/17/17/19/14/14/14  
Whi/POC F/M: 4/3/5/4/3/3/3  
POC F/M: 0/0/0/0/0/0/0  
White F/F: 1/0/1/2/3/2/2  
Whi/POC F/F: 2/2/2/1/1/1/1  
POC F/F: 0/0/0/0/0/0/0  
White Gen: 2/3/4/4/4/5/7  
Whi/POC Gen: 0/0/0/0/1/0/0  
POC Gen: 0/0/0/0/0/0/0  
All Other Types: 9/9/10/12/9/8/7]

As with the last few analyses, it is clear from this graph that a shift occurred on AO3 around 2017. White M/M pairings peaked in 2014, which was followed by a brief surge in F/M fic around 2016, before the graph was ultimately filled by POC M/M pairings - again, largely from Anime, Manga and K-Pop fandoms. Usage of Gen tags (tags with an &, indicating a platonic relationship) has also steadily increased over time. With the exception of these trends, the proportions of each category have remained close to constant, which is not surprising due to the generally slow turnover speed of the annual list.

It it worth highlighting that, since the inception of this project in 2013, the Overall Top 100 list has never included any non-M/M pairings between two People of Colour.

[Transcription: a stacked line graph titled "Ship Gender and Ethnicity in the AO3 Ship Stats Yearly List. The data is as follows:

Year: 2016/2017/2019/2020  
White M/M: 36/32/32/29  
Whi/POC M/M: 7/11/7/4  
POC M/M: 16/19/23/35  
White F/M: 14/11/13/9  
Whi/POC F/M: 3/3/2/2  
POC F/M: 0/2/0/2  
White F/F: 3/4/3/1  
Whi/POC F/F: 2/3/2/1  
POC F/F: 1/0/0/1  
White Gen: 6/5/6/5  
Whi/POC Gen: 0/1/0/0  
POC Gen: 0/0/1/3  
All Other Types: 12/9/11/8]

The Yearly lists started too late to get a clear comparison before and after the shifts taking place around 2016-2017. However, we can see that the number of M/M POC ships has steadily grown at the expense of White and Whi/POC relationships of all genders. M/M relationships between POC became the most dominant section of the Yearly Top 100 in 2020, overtaking White M/M for the first time.

A small number of non-M/M relationships between two POC have appeared on the Yearly lists at times, although these generally have relatively quick turnover that has prevented them reaching the fic totals necessary for the Overall list.

**Notes for the Chapter:**

> This is the last planned analysis in this series - if you have suggestions for other data you'd like to see, please let me know!


End file.
